Lithium-ion battery State-of-Charge estimation based on an improved Coulomb-Counting algorithm and uncertainty evaluation

An accurate estimation of the State-of-Charge (SoC) for a battery is the key to designing an efficient Battery Management System (BMS). This is due to the fact that SoC cannot be accessed directly. There are many factors leading to inaccurate estimation of SoC including battery model inaccuracies, parametric uncertainties, the nonlinearity of the battery system, battery capacity fade due to charge/discharge cycles, and temperature- and time-dependent characteristics. This paper presents a mathematical model to precisely estimate the SoC of a Lithium-ion battery based on an improved Coulomb-Counting (iCC) algorithm and uncertainty evaluation over a ten-year period. Experimental measurements using a 12V100Ah Lithium-ion battery are conducted to evaluate the performance and effectiveness of the proposed model. The obtained results indicate that the maximum estimation error using the proposed method is 0.3%, which verifies the high accuracy of SoC estimation compared to other analytical and heuristic approaches.